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Chat with Lyzr Agent

lyzr_chat

Send a message to a Lyzr agent and obtain its response, enabling direct interaction with AI agents for query resolution and task automation.

Instructions

Send a message to a Lyzr agent and get its response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesThe user message to send
user_idNoEnd-user identifier (default: default_user)
agent_idYesThe agent_id to chat with
session_idNoConversation/session id for continuity across turns
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already indicate this is a state-changing, non-idempotent call (readOnlyHint=false, idempotentHint=false). The description adds no additional behavioral context, such as the fact that it will persist conversation history or that it is a blocking call expecting a single response. This is acceptable because annotations cover the safety profile, but the description itself contributes little.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single 10-word sentence that is front-loaded with the action and outcome. Every word earns its place with no wasted content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple request/response chat tool with 4 well-described parameters and clear annotations, the description is largely complete. It could be slightly enhanced by noting non-streaming behavior or referencing session_id for multi-turn continuity, but these are already captured in the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All four parameters (message, user_id, agent_id, session_id) are fully described in the input schema with clear descriptions, so the schema handles parameter semantics. The tool description contributes no additional parameter context, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Send' with the resource 'Lyzr agent' and outcome 'get its response,' making the core function clear. However, it does not differentiate from sibling chat tools like lyzr_stream_chat or lyzr_chat_with_file, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to choose this tool over alternatives such as lyzr_stream_chat (streaming) or lyzr_chat_with_file. There are no exclusions, prerequisites, or use-case hints, leaving the agent to infer appropriateness.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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